Storage systems are subject to loss of stored data because of hardware or software failures. In order to protect and restore data in the event of a failure, storage systems utilize conventional techniques, such as, Redundant Array of Independent Disks (RAID) or Just a Bunch Of Disks (JBOD). However, in such conventional techniques, high data spaces and data protection is required for data restoration, when the degree of failure is high. By way of an example, a cluster in a storage system under RAID protection of 10 TB has only 5 TB usable space. Rest half of the total space is reserved for data protection in order to duplicate or mirror the data in the used space for backup or recovery, during failure. Moreover, these conventional techniques are not time efficient, as huge amount of data is consumed to recover data from disk array enclosures. The latency time increases rapidly when the data is dumped into parity drives. As a result, the customer has to keep on increasing the space for storing new sets of data, which is not a cost efficient method for customers, especially, Online Transaction Processing (OLTP)/A1 customers.
In some configurations, these conventional techniques can sustain up to two to three disk (or drive) failures. Beyond this, a cluster within the storage system or the whole storage system enters into the shutdown mode. As a result, the cluster reaches a data loss state, thereby interrupting customer services. Therefore, at least for the reasons cited above, such techniques are not efficient or robust for handling data for very large enterprise that operate round the clock.